Protein Folding Visualizer

An interactive web application for real-time protein structure prediction and visualization. It leverages ESMFold AI (Meta AI) to generate 3D structures and 3Dmol.js for in-browser visualization.

Features

• AI-Powered Prediction: Generate PDB structures from amino acid sequences using ESMFold
• Interactive 3D Visualization: Rotate, zoom, and explore protein structures in real-time
• Folding Animation: Watch proteins fold step-by-step through the model's "recycle" iterations
• Intuitive Controls: Interactive slider with automatic playback (Play/Pause)

Prerequisites

• Python: Version 3.10 or higher
• GPU (recommended): NVIDIA graphics card with CUDA support for faster predictions

Installation

1. Clone the Repository

git clone <repository-url>
cd protein-folding-visualizer

2. Create Virtual Environment

python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install PyTorch

For GPU support (NVIDIA CUDA 12.x):

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

For CPU only:

pip install torch torchvision torchaudio

4. Install Dependencies

pip install -r requirements.txt

5. Verify Installation

Check GPU availability (optional):

python -c "import torch; print(torch.cuda.is_available())"

Usage

Start the Application

uvicorn api.main:app --host 0.0.0.0 --port 8000

The server will start at http://localhost:5000

How to Use

1. Enter a Sequence: Paste an amino acid sequence (single-letter codes: A, C, D, E, F, G, H, I, K, L, M, N, P, Q, R, S, T, V, W, Y)
2. Predict Structure: Click "Predict Structure" and wait for processing
3. Explore the Model: Use mouse controls to rotate and zoom the 3D structure
4. Watch Folding: Use the timeline slider or Play button to animate the folding process

📁 Project Structure

protein-folding-visualizer/
├── requirements.txt       # Python dependencies
├── templates/
│   └── index.html        # Frontend interface
├── static/
│   ├── css/
│   │   └── style.css     # Styles
│   └── js/
│       └── main.js       # Client-side logic
└── README.md             # This file

Technologies

• Backend: Flask (Python)
• AI Model: ESMFold (Meta AI)
• 3D Rendering: 3Dmol.js
• Deep Learning: PyTorch with CUDA support